A
licenseA
qualityD
maintenanceMCP server for AI image generation and editing using Google Gemini image models.
7
1,166 npm
MIT
gemini-image-mcp
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TDQS
A4.1/5.0
Scored across 2 tools
Disambiguation4/5
The two tools are largely distinct: one performs AI-powered generation/editing via Gemini, the other does local sharp-based processing. However, both support background removal, which could cause slight confusion, though the descriptions clarify the difference in approach and cost.
Naming Consistency5/5
Both tool names follow a consistent verb_noun pattern (generate_image, process_image) using snake_case. The naming is clear, predictable, and parallel.
Tool Count3/5
With only two tools, the server feels thin for a general-purpose image MCP. While they cover both AI generation/editing and local processing, the scope might benefit from additional tools like image analysis or format conversion, but this is borderline.
Completeness4/5
The core workflows of generating images from text, editing with reference images, and local image processing are covered. Minor gaps exist, such as no explicit tool for image analysis or advanced compositing, but the two tools together handle most primary use cases.
Maintenance
ActivityMaintained
ResponsivenessNo issues